Abstract
BACKGROUND: Chronic kidney disease (CKD) has emerged as a significant challenge to human health and economic stability in aging societies worldwide. Current clinical practice strategies remain insufficient for the early identification of kidney dysfunction, and the differential diagnosis of immunoglobulin A nephropathy (IgAN) predominantly relies on invasive kidney biopsy procedures. METHODS: First, we assessed a case-control cohort to obtain urine samples from healthy controls and biopsy-confirmed CKD patients. Matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) was applied to detect urinary peptide and then these urinary peptide profiles were used to construct diagnostic models to distinguish CKD patients from controls and identify IgAN patients from other nephropathy patients. Furthermore, we assessed the robustness of the diagnostic models and their reproducibility by applying different algorithms. RESULTS: A rapid and accurate working platform for detecting CKD and its IgAN subtype based on urinary peptide pattern detected by MALDI-TOF MS was established. Naturally occurring urinary peptide profiles were used to construct a diagnostic model to distinguish CKD patients from controls and identify IgAN patients from other nephropathy patients. The performance of several algorithms was assessed and demonstrated that the robustness of the diagnostic models as well as their reproducibility were satisfactory. CONCLUSIONS: The present findings suggest that the CKD-related and IgAN-specific urinary peptides discovered facilitate precise identification of CKD and its IgAN subtype, offering a dependable framework for screening conditions linked to renal dysfunction. This will aid in comprehending the pathogenesis of nephropathy and identifying potential protein targets for the clinical management of nephropathy.